Reward-circuit biomarkers of risk and resilience in adolescent depression.

Journal of affective disorders(2018)

引用 61|浏览15
暂无评分
摘要
BACKGROUND:Dysfunctional reward processing is a core feature of major depressive disorder. While there is growing knowledge of reward processing in adolescent depression, researchers have ignored neural mechanisms of resilience to depression. Here, we examine neural correlates of reward processing that characterize resilience and risk in adolescents at risk for depression, facilitating the development of effective intervention approaches that strengthen resilience to psychopathology in at-risk youth. METHODS:50 adolescent females were followed through age 18: 32 at-risk adolescents who either did (remitted-depressed; n = 15) or did not (resilient; n = 17) experience a depressive episode, and 18 low-risk healthy controls. Participants completed clinical assessments at 18-month intervals and an fMRI reward-processing task in late adolescence. We conducted predictive modeling with a priori reward regions of interest (ROIs). RESULTS:At-risk resilient and remitted-depressed adolescents exhibited less striatal activation than did controls during anticipation of reward. Resilient adolescents exhibited greater activation than did remitted-depressed adolescents in the middle frontal gyrus during reward anticipation, and less activation in the superior frontal gyrus and cuneus during processing of reward outcome. Using predictive modeling, ventral anterior cingulate cortex and putamen activation during reward processing distinguished resilient from remitted-depressed adolescents with 83% accuracy. LIMITATIONS:The relatively small sample size of only females and the fact that fMRI data were obtained at one time point in late adolescence are limitations. CONCLUSIONS:Distinct patterns of neural activation in reward circuitry appear to be markers of risk and resilience that may be targets for prevention and treatment approaches aimed at strengthening adaptive reward processing in at-risk adolescents.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要